Learn about the basics of Teradata architecture and why it’s still a top RDBMS for Data Warehousing. Discover how the system is built for parallelism and how hashing algorithms help distribute data evenly among AMPs. Explore the essential roles of Parsing Engines, AMPs, and Nodes in executing instructions and managing resources.
Learn how to efficiently add new partitions to a Row Partitioned Table. We compare two methods, ALTER TABLE and INSERT…SELECT, with test results.
Learn how to handle rounding issues in Teradata with this helpful article. Discover a possible solution to a common problem and improve your results!
Learn how to optimize Teradata SQL Tuning with comprehensive analysis of available tools in this article. Discover the optimal approach for query optimization for both tactical and strategic workloads, as well as methods for eliminating full table scans, reducing skew, and examining the execution plan. Plus, find out how to address common issues like concurrency and misestimation.
Learn about Teradata Spool Space, a temporary workspace used to store intermediate and final result sets. Discover ways to increase and manage Spool Space.
Learn the differences between Teradata SUBSTR and SUBSTRING functions for string manipulation. Discover the syntax variations, parameters, and usage examples.
Discover the differences between Teradata MULTISET and SET tables for effective data modeling. Learn how to avoid duplicates and improve performance.
Discover the power of Teradata FastLoad – the bulk load utility that efficiently loads vast amounts of data, bypassing the transient journal. Learn more here.
Learn about Teradata Volatile Tables, their features, restrictions, and performance tuning possibilities. Find answers to common questions about their usage.
Avoid data warehouse project failures by choosing the right data model. In this article, we explore denormalization techniques for when it makes sense, including repeating groups, prejoins, and derived information. We also discuss alternatives to denormalization, such as Global Temporary Tables and Volatile Tables. Remember, denormalization can improve performance but has significant drawbacks and should be used only when necessary.
Expert network for enterprise data platforms. Senior consultants, project teams built for your challenge — across Teradata, Snowflake, Databricks, and more.
📍Vienna, Austria & Miami, Florida
Join 4,000+ data professionals.
Weekly insights on Teradata, Snowflake & data architecture.